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Open Access Publications from the University of California

Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings

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The paper introduces a hybrid modelling approach that enhances the accuracy and usability of physics-based energy simulation for existing buildings. The approach leverages measured zone air temperature data streams—increasingly available from smart thermostats—to derive difficult-to-obtain input parameters for internal thermal mass and infiltration airflow rates. It does so using a reformulated inverse heat balance algorithm. We implemented the inverse algorithms in EnergyPlus and used LBNL's Facility for Low Energy eXperiments (FLEXLAB) for demonstration and validation.

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